Introduction 

In the mid-twenties, when the brain stops developing, is when you begin to go into cognitive decline, and your cognitive functioning process may slow down. A large body of literature has showcased that people experience losses in their memory as they start to age. Most cognitive tests that are created give insight into an applicant’s ability to use their mental processes to complete a task or to solve problems. Anyone who approaches this type of research on cognitive tests must keep in mind the possibility of cultural and racial bias in some of these particular tests. “The Wechsler Adult Intelligence Scale (WAIS) exam measures the working memory and processing speed within adults, however this test is only available in English and Spanish. Therefore, cognitive tests that are still well used today are for specific audiences and have a disregard for any other native speaking languages, and they deserve to undergo cognitive testing with the same materials that English and Spanish receive, because neither race nor age should be a defining matter in getting properly tested. 

For the purposes of this research, the main points of this paper include: dates when these tests were created, what country they were created in, who they were created for along with why they were created in the first place, before the tests could be considered reliable and if they should still be used today. Additionally, to further the understanding of cognitive tests, a meta-analysis was conducted to analyze the fundamentals of age groups and how they differ in results. The reason for this meta-analysis was to view different types of cognitive tests and their accountability when it comes to how effective their tests are, and if they could still be used today. As some of the cognitive tests that were studied came out in the 1990s to 2010, most of them don’t take into account people who speak different languages, people who have disabilities, and ect. 

 

Literature Review 

Brain Functions In Cognitive Tests 

 All cognitive tests measure a variety of different brain processes that include learning, thinking, using judgment, as well as language. One commonality that is recurrent in these exams is their ability to measure out the way the brain carries out different cognitive functions. One may think they could be more efficient in one intelligence than the other, however, these types of intelligence fluctuate throughout one’s life and vary among ages. Fluid intelligence is said to decline through adulthood, although crystallized abilities show greater gains in older people (Tucker-Drob, 2022). These two types of intelligence work together as fluid intelligence in how able someone can retain new information and solve problems. Many psychologists utilize cognitive tests to view problems with how the brain processes thoughts, and it is important to realize they are testing pertaining to specific cognitive processes.

 Not all cognitive tests are going to look the same; that’s the opening for inconsistencies because even though they are not the same, all cognitive tests seek results revolving around thinking processes. For example, a person with Alzheimer’s would show changes in their executive functions including problem-solving, memory, and their ability to perform tasks (Stanford Medicine, 2017). When a psychologist administers the exam, they have to take into account how old their patient is and any disabilities they may have. Cognitive functioning is something every brain experiences, however each one works differently. Cognitive exams help assess how the brain processes information, which is important for making accurate diagnoses.

 

Memory  

Psychology encompasses so many different parts of the brain so it’s important to gain a richer understanding of psychology so individuals can gain insights into their actions and start to gain a better understanding of other people. Your memory is the continued process of information that you collect over time. Memory allows individuals to draw upon past events and be able to connect those memories to tests they would potentially have to take in the present. The working memory specifically references a function in your brain that uses temporary storage and manipulates different pieces of information, which is a necessity for complex cognitive tasks (Baddeley, 1992). The most important changes of the brain that have to do with age consist of declines in performance on cognitive tasks like the process of transferring information to make a decision.

Piaget mentions that the last stage is the ability to understand theories and abstract ideas; however, he fails to establish that the formal operational stage is broken down further because of the way the brain develops depending on what age a person is currently at (Feldman, 2005). As an older person completes a cognitive test, their sensory perception and processing speed decline with their age, which would impact their test performance in many of their cognitive domains (Murman, 2015). There is a clear decline in cognitive functions in older adults because they perform cognitive activities more slowly than young adults, as they cannot focus on specific information while simultaneously ignoring irrelevant information.

 

A Meta-Analysis Effect Size

A meta-analysis is used to see if there is any statistical significance within any research. Meta-analyses use effect sizes to identify consistent relationships between variables or differences among age groups (Durlak, 2009). Effect sizes can vary from small to large; the smaller the effect size, the more limited the findings will be, and the larger the effect size, the more significance your research has because it reaches out to varying audiences. As Zhongheng Zhang 2013 conducted a meta-analysis on critical care medicine, his larger trials showed to have a significantly better response quality than his smaller trials in sample size collection, intention to treat, sequence generating, etc. (Zhang et al, 2013). Effect sizes are important because they help the meta-analysis become plausible, showing why it connects to the majority and not just a select number of people.

 When a meta-analysis establishes its effect size, they have to back itself up in why and how it chose that specific group; otherwise, its studies cannot be done by another researcher. Many primary studies fail to provide information on how effect sizes are selected and computed, which leads to the calculations of mean effect sizes encountering small discrepancies (Maassen, 2020). Effect sizes need to be conducted to show that your research does not have any inflicted biases and it reaches out to more than one specific audience. 

 

Types Of Meta-Analyses
Meta-analyses are written on many things like teaching, psychotherapy, formal language, children and more. However, based on the provided literature within this review, there seems to be a lack of studies that include any sort of meta-analysis conducted on the study of other cognitive tests. Many of the cognitive tests studied in this research all look for the same results in cognition however, many of them fail to showcase the age differences. “The 5-cog cognitive test” was created to detect cognitive decline in older adults. It’s a collection of cognitive tests that measure attention, memory, visuospatial, language, and reasoning (Sugiyama, 2015). The subtests that are within “The 5-cog” are highly correlated to neuropsychological exams that both measure the same cognitive domain. As a result, “The 5-cog cognitive test” is a tool for groups that shows significant reliability and validity in detecting cognitive impairment in older adults (Sugiyama, 2015). However, this cognitive test fails to determine what they mean when they use the term “older people”, which could mean that their effect size might have small discrepancies because they did not specify the tested group of people. 

There has been a meta-analysis written on neuropsychological test performance on people who have Attention-Deficit/Hyperactivity Disorder (ADHD), written by Eric A. Youngstrom, 2004. This meta-analysis compared healthy participants with those who have ADHD to examine the differences in cognitive processes. As the participants who had ADHD showed a higher full scale IQ than the other participants, Youngstrom knew this raised a red flag, so he then took it a step further and computed the weighted mean effect size and the test for the significance in their effect size by comparing them in groups instead of individually. All ADHD groups showed a lower score when combined and then compared to the entire group of healthy participants (Youngstrom, 2004). This paper highlights the importance of calculating effect sizes by demonstrating that results can vary significantly when comparisons are made on a larger scale. 

This paper intends to add to continuing research by viewing the dynamics of a meta-analysis in greater detail, while also viewing how efficient cognitive tests are and whether they should still be considered for use today. Using a quantitative approach, the main goal is to examine how meta-analyses report and utilize effect sizes, particularly concerning different age groups. This includes a comparison of cognitive tests to determine which ones are most effective at assessing cognitive function in older adults. Since younger age groups generally perform at a significantly higher cognitive level, there’s little value in using them as a benchmark when evaluating the cognitive abilities of older populations.

   

Method 

Design 

This research paper explores the connection between cognitive tests and their validity in concluding their results when taking into account their dependent variables, effect sizes and if any of the current tests have racial or cultural biases. This is a study of a qualitative analysis research design by looking at two or more dependent variables with the researcher having to control one of those variables. To be included in this meta-analysis each cognitive test had to be used in more than three studies, had to test/measure for memory, processing speed, retrieval or pattern recognition and had to be tested on older adults. This design was created in order to figure out what cognitive tests are the strongest by imputing all their data into an Excel sheet and concluding their pooled standard deviation, mean difference and their effect size. In finding the strongest cognitive test, the researcher will then be able to compare the rest of the cognitive tests to the control in order to find out which ones are optimal and non-optimal.

 

Materials

For the meta-analysis, there was a list of various cognitive tests that were used in order to find a control test which would be the strongest and be able to compare all the other cognitive tests to that test by not only looking at their bell curves but also their effect sizes. Essentially, all of these cognitive tests were tested for cognitive functions within younger and older adults and aimed for functions of memory, recall, and pattern recognition. While all the tests aimed to figure out the same thing, some of them possibly didn’t calculate their results the correct way, and the study aims to find out if any of the selected cognitive tests are non-optimal based on the control cognitive test within the meta-analysis. The main objective of this research was to figure out if there needs to be a new cognitive test created because the ones we use today are considered inconsistent due to a lack of fixation among all age groups. If it is found that all the cognitive tests are consistent with the control then there will be no need to implicate a new cognitive test as there were no inconsistencies between them. 

Procedure 

In order to complete the meta-analysis, the researcher first had to find cognitive tests that worked with age groups that involved people over the age of 65 to clearly view how these tests determine cognitive decline within senior citizens and not have the influence of only teenagers. Before coming up with a concrete list, the cognitive tests were also put through subgroups like Sex, Gender, Sample Size, ect; in order to ensure the cognitive tests that were picked validated toward this study. Means and standard deviations, as well as effect size, were then used to determine the order of the cognitive tests. This ultimately led to using the “Mini Mental State Exam” as the control and the “Mini – Cog” ranking the lowest cognitive test out of all six that were included in this study due to a completely  skewed bell curve insisting that a giant chunk of their collected data was not included in their final results.

Having the highest mean was important because it is used for the measure of central tendency which uses all values in the data set to give an overall average of the set. The significance of standard deviation lies in the fact that it provides a mark of how far the individual responses to a question “deviate” from the mean. Having a lower standard deviation is better because it shows that the data is huddled tightly around the mean which ensures that it is more reliable instead of a larger standard deviation which has more variance in its results. Lastly, effect size had to be looked at because it shows how meaningful the relationship between variables are and the differences between different age groups are. 

As the control test was found, the researcher then had to create bell curves for each test in order to visually view if there are really any differences between the cognitive tests as a whole. In order for the researcher to create bell curves they had to establish values by using the gap and 99.7% low/high. The reason for using 99.7% is because the empirical rule expresses that the percentage of data observed has to lie within three standard deviations that follow the mean in order to be considered a normal distribution. The empirical rule tells us where most of the values in a particular study lie within their normal distribution, therefore it showcases how spread out all the data is away from its mean. The standard deviation is a crucial part in statistical analysis for understanding the variability of a dataset; they help identify trends, detect outliers, compare data sets and evaluate risks. Once the bell curve was created using Excel, the researcher then calculated the z-score for each value in order to find out how many standard deviations each score was close or away from the mean. 

The z-score provides a statistical measurement that shows a value’s relationship to the mean of the overall values. Once every curve was established the researcher then was able to compare each bell curve to the control by looking at how well the graphs matched, if they had the same z-scores and how far they skewed either to the left or the right. The purpose of the bell curves is to visually see if there are any differences between the cognitive tests, instead of looking at just the numbers because they could be misleading depending on how big or small the study was. The last test that was used was the Dixon’s Q tests in order to either identify or rule out any outliers within the data set. A Dixon Q data assumption comes from a normal distribution, because of this it is strongly recommended that the Dixon test be partnered with a normal probability test. One of the main tests used was the bell curves and for this reason a Dixon Q test was a need in order to make sure that the data numbers matched up. 

 

Results 

Quantitative Analysis Results 

As the “Mini Mental State Exam” was the control; their sample size consisted of 1,569 participants and 80% of that sample size passed the exam. Of the other five cognitive tests that were analyzed only three of them matched up to the control group. As each test had its own set of values pertaining to their bell curve, four of them (“Mini Mental State Exam, “Moca Cognitive test”, “Number symbol coding task”, and the “TYM cognitive test”) had the same exact z-scores even though all their values were different. Having the same z-scores (-3 to 3) prove that all their data is both closely clustered to the mean as well as spread out. The “Mini-Cog” and the “Wechsler Adult Intelligence Scale ” tests not only have different z-scores but their bell curves are completely skewed to the right and majority of their data is laid outside their bell curve. The skewness to the right showcases that there is an imbalance distribution of data, where their mean is larger than the median and there will be a concentration of data points that is higher at the end of the curve. Due to the graph being skewed there is no clear point, where a normal distribution will have its median, mean, and mode equally distributed around the middle of the data set. 

            A bell-curve is most helpful because it can be used to describe many populations ensuring that there is no bias towards one specific age group. When looking at the curves, it is important to realize that they approximate many natural occurring phenomena accurately and they are relatively easy to solve requiring only the mean and standard deviation. These six bell curves showcases the data for each cognitive test starting with the control test (Mini Mental State Exam) followed by the other cognitive tests. The bell curves were a creative process used to visually see if the cognitive tests had any similarities or differences. The bell curves made it possible to show that most of the cognitive tests are in fact the same and have the same shapes even though their data looks completely different. 

 

Figure A 

Bell Curve for the “Moca Cognitive Test” which mirrors the control cognitive test that shows it really isn’t any different. 

 

Figure B

Bell Curve for the “Mini-Cog” that shows a completely skewed bell curve to the right which is not good because it does not mirror the control test. 

 

Figure C

The bell curve for the “Wechsler Adult Intelligence Scale” which also has a skewed bell curve that shows it does not mirror the control cognitive exam. Was also the lowest ranking cognitive test. 

 

Figure D

Bell curve for the “TYM Cognitive Test” does in fact mirror the control test which shows that even though they are different tests they still match up to each other. 

 

Figure E

Bell Curve for the “Number Symbol Coding Task” again mirrors the control exam which proves that most cognitive tests match up.  

 

Figure F

Last bell curve for the “Mini Mental State Exam ” control cognitive test that all other cognitive tests are matching up to. 

 

Discussion 

The primary goal of this research was to determine whether there were any discrepancies between the cognitive tests that were used in this research paper. Regarding the initial question “How Efficient Are Cognitive Tests Based On Age And Their Effect Sizes In How They Label Dementia And Alzheimer’s”?, it is apparent that there is in fact a problem with some cognitive tests due to them cutting out a huge portion of their data making it look better than it really is. However, even though the communication of different cognitive functions has been talked about non-stop over time, it is beneficial to acknowledge all people have different cognitive functions due to age, gender, and race which is why cognitive exams have to be truthful to all the people that they test. Despite most cognitive tests matching up to the control in this study, the findings prove the initial hypothesis that there are in fact discrepancies between some of the cognitive tests because the completely skewed bell graphs show that these exams are purposely cutting out the data that would rank their test lower. 

Overall, the findings within this paper agree with the initial hypothesis stating that even though all cognitive tests should be on the same wavelength there were found discrepancies that showcase all cognitive tests do not tell the truth. The use of the bell curves in this paper were found to be more effective to communicate these messages because only looking at their numbers leaves room for the normal eye to miss these discrepancies, regardless of the many tests that were also used to support it. 

Limitations 

Let it be apparent the amount of cognitive tests that the researcher was able to use should be mentioned, because as their research progressed there were more and more tests that did not make the cut and had to them out. This would impact the results because they needed to find more cognitive tests but if they couldn’t then they had to work with the number they had. The use of the bell curves ensured that two of the cognitive tests were completely off when being compared to the control cognitive test and the tables in this paper only showcased that the cognitive tests had little to no differences.The biggest limitation while picking out the cognitive tests were the age groups they choose to use because the original hypothesis stated that older people are being labeled inaccurately due to being compared to age groups that would without a doubt have higher cognitive levels.  Due to this; the cognitive tests had to be testing older adults and not teenagers or little kids. 

Implications 

The bell curves were the most important finding generated by the method used in this research paper by being able to form a new understanding because it visually showcased the discrepancies between all the cognitive tests that were used in this study. When looking at all of the data charts it is evident that most of the numbers look identical and it’s hard to see the pattern that was hidden behind them.  In order to reach an conclusion the researcher had to focus on the data that came from the bell curves and not the data that came from the tables because the bell curves were statistically significant when it came to determining that there were problems with some of the cognitive tests that we use and it is not fair to older people who have the right to be tested, but are only being tested while being compared to various age groups. If the researcher was to rely on the tables themselves then their hypothesis would have not only been proven wrong but it would have shown that none of these cognitive tests are absorbingly different. The two cognitive tests that did not match up were “The Mini-Cog” and the “Wechsler Adult Intelligence Scale”. They did not only have different z-scores but all of their data did not fit within the curve which proved that they are non-normal distributions. A non-normal distribution shows that the data set is too far away from the mean which indicates the data is less frequent in occurrence. Including all your data is a crucial part in explaining your results because it established that they took everything in and did not just include the parts that they wanted to publish to the world. 

 

Conclusion 

Cognitive tests were created to measure cognitive abilities across all age groups. Many of the cognitive tests reviewed here demonstrate that not all consider age, disabilities, and effect sizes. Cognitive decline is something that will be apparent in older people for the rest of time, showcasing a dynamic platform for the creation and dissemination of new cognitive tests and theories that revolve around the brain. The decline of cognitive functions will undoubtedly keep evolving to new theories and developments in our constantly connected world as more and more research expands on this topic. Studying the brain not only offers an interesting perspective into how the brain is constantly changing, but it also emphasizes how crucial cognitive functions are pertaining to these functions being measured the correct way. Many different groups of people involving age, race, gender, and disability are not always being tested fairly and it is the job of cognitive tasks to rightfully examine how functions in your brain work and determine, if any, cognitive defects without being interfered with by any other age group. At that stage who really knows their cognitive level if they aren’t being diagnosed right, it’s worse for the older generation because a diagnosis based on their cognitive abilities could be a defining step in their future. The proper communication is the next step for taking these cognitive tests and making them better for our community. 

References

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Durlak, J. A. (2009). How to select, Calculate, and interpret effect sizes. Journal of Pediatric Psychology, 34(9), 917–928. https://doi.org/10.1093/jpepsy/jsp004

Maassen, E., Van Assen, M. A., Nuijten, M. B., Olsson-Collentine, A., & Wicherts, J. M. (2020). Reproducibility of individual effect sizes in meta-analyses in psychology. PLOS ONE, 15(5), e0233107. https://doi.org/10.1371/journal.pone.0233107

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Zhang, Z., Xu, X., & Ni, H. (2013, January 9). Small studies may overestimate the effect sizes in critical care meta-analyses: A meta-epidemiological study. Critical care (London, England). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4056100/  

 

Appendix A

Table 1 

First requirements for each cognitive test to be applicable for this study 

Cognitive Tests				Number of Participants	Age Group	Accessibility	Sex
The 5-Cog test (Uses older adults, while using two different races/genders)				1,200 participants total	65 and older	Two page paper and pencil test	Black and Hispanic men and women
The Neuropsychiatric Inventory questionnaire (Smallest Effect size)				60 participants total	67 and older	Two page self – administered questionnaire not an interview.	Alzheimer’s patients male and female
The Mini Mental State Exam (Biggest Effect size)				1,569 participants total	Doesn’t give a specific age group	30 question assessment (pen and paper)	Men and Women with potential dementia or alzheimer’s disease
The Number Symbol Coding Task (Test with the biggest age group)				400 participants total	38 to 98 years old	90 second executive task that includes attention, planning and set switching	Patient-caregiver dyads =both male and female
The Moca Cognition Tests (Specifically targeting Mild cognitive impairment)				210 participants total	18 to 70	Screening test for Mild cognitive impairment	Healthy participants both male and female
The CogAT Test (Test with the youngest age group)				16,386 total but not all parts completed	7 and 8 year olds	Is given on the computer with the exception of the pencil and paper bubble sheet	Second Graders both male and female as well as multiple races
The Wechsler Adult Intelligence Scale (Only test that used young adults, and only one to be taken by being guided)				250 Adults	18 to 24 years old	Individually assessed by a psychologist or educator trained to apply the WAIS-IV in accordance with the administration manual	Adults both male and female in Egypt
Raven’s Standard Progressive Matrices (Age group is only teenagers)				99 participants total	13 to 16 years old	Participants completed the tasks on a laptop or tablet in a classroom setting with 19 to 27 students present.	Dutch – High school students both male and female
The Mini- Cog				1,515 participants	Doesn’t give a specific age group	Test is written on paper and there is a part of the test where someone is talking to you	Men and Women who had dementia and did not have dementia
TYM Cognitive Test				157 participants	41 to 83 years old	Test is written on paper and there is a part of the test where someone is talking to you	Men and Women who had dementia from a specialist memory clinic

 

Note. The first table created was the first few requirements from the tests in order to move to the next table. All tests labeled in red did not make the cut and could not move forward to the next table. The first requirements include gender, sex, and number of participants in order for all cognitive tests to be on the same wavelength, making sure that no cognitive test has an advantage. 

Appendix B

Table 2 

Second amount of requirements for each cognitive test 

Instrument	Time to use  (min)	Gold Standard	Cutoff	Sensitivity	Specificity
Scale 1-8
The 5-Cog test	3 to 5 minutes	Independent clinical diagnosis of dementia	Probably normal/ possibly impaired	0.76%	0.89
The Neuropsychiatric Inventory questionnaire	15 minutes or longer	Behavioral Pathology in Alzheimer’s Disease Rating Scale (Behave-AD)	5 out of 55	2%	5%
The Mini Mental State Exam	10 minutes	Quality assessment using the QUADAS‐2	24/23	23% to 76%	40% to 94%
The Number Symbol Coding Task	90 second task	Clinical Dementia Rating (CDR), patient and caregiver versions of the Quick Dementia Rating System (QDRS)	36	0.88%	0.76%
The Moca Cognition Tests	10 minutes	Clinical diagnosis of Alzheimer’s disease	26	95%	37%
The Wechsler Adult Intelligence Scale	60 to 90 minutes	The Wechsler tests have long been regarded as the “gold standard” in IQ testing.	14/25	Doesn’t give	Doesn’t give
The Mini-Cog	5 to 10 minutes	Independent clinical diagnosis of dementia	Probably normal/ possibly impaired	0.76 to 1.00	0.27 to 0.85
TYM Cognitive test	About 5 minutes	DSM-IV dementia	42/50	0.8	0.84

Note. Second table using different factors in order to see if they qualify for this specific study. These factors were chosen to ensure that each test could be on the same wavelength and they wouldn’t be too far apart while being compared. All tests highlighted in red are again cut out. 

 

Appendix C 

Table 3 

Table that lists all the Means and Standard Deviations of each cognitive test that made it through the study in order to see which test had the highest, helping put them in order from optimal to non-optimal 

		Mean	Standard Deviation	Number of People		Year
Best Cognitive test : The Mini Mental State Exam (Control)		39.1 (Second highest)	11.23(Fourth lowest)	1,569		2015
The Moca Cognitive test		25.5(Fifth Highest)	22.1(Highest Standard Deviation)	210		2020
The Number Symbol Coding task		30.1(Fourth highest)	13.8(Fifth lowest)	400		2020
The Mini-cog		82.4(Highest Mean)	3.4(Second lowest)	1,515		2018
TYM Cognitive Test		34.4(Third highest)	9(Third lowest)	157		2019
Worst Cognitive test: The Wechsler Adult Intelligence Scale		20.65(Lowest Mean)	1.71(Lowest Deviation)	250		2021
		EFFECT SIZES
Color Key For Mean and SD		Effect Size Between MMSE and Moca Cognition = 0.8 (-0.8) Had to switch the order of means to get a positive effect size
Yellow = Highest Mean                Yellow = Lowest Standard Deviation		Effect Size Between MMSE and Number Symbol Coding task = 0.7 (-0.7) Had to switch the order of means to get a positive effect size
Blue = Second highest (Mean)   Blue = Second lowest (Standard Deviation)		Effect Size Between MMSE and The Mini-cog = 5.9
Purple = Third highest (Mean)   Purple = Third lowest (Standard Deviation)		Effect Size Between MMSE and TIME Cognitive test = 0.4 (-0.4) Had to switch the order of means to get a positive effect size
Green = Fourth highest (Mean)  Green = Fourth lowest (Standard Deviation)		Effect Size Between MMSE and The Wechsler Adult Intelligence Scale = 2.8 (-2.8) Had to switch the order of means to get a positive effect size
Orange = Fifth highest (Mean)   Orange = Fifth lowest (Standard Deviation)
Red = Lowest Mean                  Red = Highest Standard Deviation

 

Note. Final table, a total of six cognitive tests made the cut. Mean and standard Deviation were color coded due to one of the important factors being highest mean and lowest SD. Effect sizes were also calculated between the control test compared to the rest. 

 

Appendix D

Table 4 

“Mini Mental State Exam”(Control test) values in order to create their bell curve and move along with comparing these values to all other values from each cognitive test. 

Name Of Cognitive Test	Percentage Passed	Values	Normal Values		Particulars	Values
Mini Mental State Exam	80%	5.41	0.000394644		Mean	39.1
Moca Cognitive Test	63%	18.886	0.00703029		Standard Deviation	11.23
Number Symbol Coding Task	30.10%	32.362	0.029672716		99.7% low	5.41
The Mini-Cog	95%	45.838	0.029672716		99.7% high	72.79
TYM Cognitive Test	34.40%	59.314	0.00703029		Steps	5
Wechsler Adult Intelligence Scale	72%	72.79	0.000394644		Gap	13.476

Note. According to the control cognitive test(Mini Mental State Exam), all information gathered here was used to create the bell curve for this exam. 

 

Appendix E

Table 5 

“Moca Cognitive Test” values in order to create their bell curve and move along with comparing these values to all other values from each cognitive test. 

 

Name Of Cognitive Tests	Percentage Passed	Values	Normal Values		Particulars	Values
Mini Mental State Exam	80%	-42	0.000196971		Mean	25.5
Moca Cognitive Test	63%	-15	0.003508896		Standard Deviation	22.5
Number Symbol Coding Task	30.10%	12	0.014809982		99.7% low	-42
The Mini-Cog	95%	39	0.014809982		99.7% high	93
TYM Cognitive Test	34.40%	66	0.003508896		Steps	5
Wechsler Adult Intelligence Scale	72%	93	0.000196971		Gap	27

Note. According to the cognitive test(Moca Cognitive Test), all information gathered here was used to create the bell curve for this exam. 

 

Appendix F 

Table 6 

“Number Symbol Coding Task” values in order to create their bell curve and move along with comparing these values to all other values from each cognitive test. 

 

Name Of Cognitive Tests	Percentage Passed	Values	Normal Values		Particulars	Values
Mini Mental State Exam	80%	-11.3	0.000321148		Mean	30.1
Moca Cognitive Test	63%	5.26	0.005721026		Standard Deviation	13.8
Number Symbol Coding Task	30.10%	21.82	0.02414671		99.7% low	-11.3
The Mini-Cog	95%	38.38	0.02414671		99.7% high	71.5
TYM Cognitive Test	34.40%	54.94	0.005721026		Steps	5
Wechsler Adult Intelligence Scale	72%	71.5	0.000321148		Gap	16.56

Note. According to the cognitive test(Number Symbol Coding Task), all information gathered here was used to create the bell curve for this exam. 

 

Appendix G 

Table 7 

“The Mini-Cog Exam” values in order to create their bell curve and move along with comparing these values to all other values from each cognitive test. 

 

Name Of Cognitive Tests	Percentage Passed	Values	Normal Values		Particulars	Values
Mini Mental State Exam	80%	72.2	0.001303485		Mean	82.4
Moca Cognitive Test	63%	76.28	0.023220635		Standard Deviation	3.4
Number Symbol Coding Task	30.10%	80.36	0.098007236		99.7% low	72.2
The Mini-Cog	95%	84.44	0.098007236		99.7% high	92.6
TYM Cognitive Test	34.40%	88.52	0.023220635		Steps	5
Wechsler Adult Intelligence Scale	72%	92.6	0.001303485		Gap	4.08

 

Note. According to the cognitive test(The Mini-Cog), all information gathered here was used to create the bell curve for this exam. 

 

Appendix H 

Table 8 

“TYM Cognitive Test” values in order to create their bell curve and move along with comparing these values to all other values from each cognitive test. 

 

Name Of Cognitive Tests	Percentage Passed	Values	Normal Values		Particulars	Values
Mini Mental State Exam	80%	7.4	0.000492428		Mean	34.4
Moca Cognitive Test	63%	18.2	0.00877224		Standard Deviation	9
Number Symbol Coding Task	30.10%	29	0.037024956		99.7% low	7.4
The Mini-Cog	95%	39.8	0.037024956		99.7% high	61.4
TYM Cognitive Test	34.40%	50.6	0.00877224		Steps	5
Wechsler Adult Intelligence Scale	72%	61.4	0.000492428		Gap	10.8

Note. According to the cognitive test(TYM Cognitive Test), all information gathered here was used to create the bell curve for this exam. 

 

Appendix I 

Table 9 

“Wechsler Adult Intelligence Scale”(Lowest Ranking cognitive test) values in order to create their bell curve and move along with comparing these values to all other values from each cognitive test. 

 

Name Of Cognitive Tests	Percentage Passed	Values	Normal Values		Particulars	Values
Mini Mental State Exam	80%	15.52	0.002591724		Mean	20.65
Moca Cognitive Test	63%	17.572	0.046169683		Standard Deviation	1.71
Number Symbol Coding Task	30.10%	19.624	0.194868189		99.7% low	15.52
The Mini-Cog	95%	21.676	0.194868189		99.7% high	25.78
TYM Cognitive Test	34.40%	23.728	0.046169683		Steps	5
Wechsler Adult Intelligence Scale	72%	25.78	0.002591724		Gap	2.052

Note. According to the cognitive test(Wechsler Adult Intelligence Scale), all information gathered here was used to create the bell curve for this exam. 

 

Appendix J 

Table 10 

Last number comparisons to view further if the “Wechsler Adult Intelligence Scale” and “The Mini-Cog” are different from “The Mini Mental State Exam” 

Measure	N(Sample Size)	M(Mean)	Mdn(Median)	Weighted M(effect Size)	95% CI	Q
The mini mental state exam	1,569	39.1	36.5	Control	3.9 – 4.6	There is no significant difference
Number Symbol Coding Task	400	30.1	30	0.7	.82 – .91	There is no significant difference
The Moca Cognition	210	25.2	14	0.8	0.44–0.76	There is no significant difference
The Wechsler Adult Intelligence Scale	250	20.65	19.6	2.8	0.21 – 0.23	There is no significant difference
The Mini-Cog	1,515	82.4	80.36	5.9	.08 – .17	There is no significant difference
TYM Cognitive Test	157	34.4	29	0.4	.72 – 1.5	There is no significant difference

Note. Final table that uses a few more different tests in order to establish the discrepancies between The Mini Mental State Exam and the cognitive tests that are bolded because those two cognitive tests were completely skewed to the right, while the others matched up to the Mini Mental State Exam. 

 

Appendix K 

Table 11

Cognitive tests that did not make it into this study 

Tests That Did Not Make The Cut

Raven’s Standard Progressive Matrices

The CogAT Test

The 5 -Cog test

The Neuropsychiatric Inventory questionnaire

Note. Table that shows all the cognitive tests that were not applicable for this study